One approach to understanding the effects of exercise on the brain and the cortical processes underlying peak performance is to measure brain activity using electroencephalography. Electroencephalography is a noninvasive technique that uses highly conductive silver or silver chlochloride (Ag/AgCl) electrodes to record brain activity, which is also referred to as electroencephalographic (EEG) activity.
The EEG recording is actually a measure of electrical signals that are produced by neural cells in the brain and are measurable at the scalp. Because the electrical signals must pass through the dura mater, cerebrospinal fluid, skull, and skin before reaching the electrodes, these signals are recorded in a small unit of measurement called microvolts. EEG can be measured using either single electrodes (flat metal disks) that are attached at particular locations on the head or an electrode cap that has fixed electrodes sewn into the cap. The electrodes are adhered to the scalp using a specific type of gel or paste that maximizes conductance. The electrodes are connected by wires to an amplifier and a computer that records the brain activity. The internationally standardized 10–20 system developed by Herbert Jasper in 1958 is frequently used to communicate particular scalp locations used to record EEG. The locations of the sites are judged relative to landmarks on each individual’s scalp, including the bridge of the nose, the bony protuberance at the base of the skull, and the midpoints of the ears. This original system included 21 electrodes that reflect measurement at frontal (F), temporal (T), parietal (P), occipital (O), and central (C) regions of the brain (Figure 1). In this system, the odd number indicates that the locations are on the left side of the brain and the even numbers indicate that the locations are on the right side of the brain. More modern EEG systems can include electrode placements that record information from 32, 64, 128, or up to 256 sites. In addition to the electrodes that are used to record EEG from sites of interest, an additional electrode called the reference electrode is used to subtract out basal activity so that the resultant recording from the sites of interest is reflective only of activity at those sites. This electrode is typically placed on the bridge of the nose or on an earlobe.
Figure 1 Jasper 10–20 System for Electrode Identification Source: Adapted from Teplan, M. (2002). Fundamentals of EEG measurement. Measurement Science Review, 2(2), 1–11.
There are several computer software programs that can be used to record and analyze EEG data. In addition to recording EEG activity, some software programs can also be used for creating and presenting different types of visual and auditory stimuli so that EEG activity can be recorded relative to behavioral responses to those stimuli. More advanced software programs integrate EEG data with measures using other neuroimaging techniques like magnetic resonance imaging (MRI), positron emission topography (PET), and single photon emission computed tomography (SPECT) data. When collecting EEG data, there are several important things to remind participants of when preparing for the test. Participants should avoid taking certain medications that may alter the brain’s electric activity, such as sedatives, muscle relaxants, and sleeping aids. Participants should also avoid caffeine and exercise within 12 hours of the test. The use of hair spray, gels, oils, or other hair chemicals should be avoided on testing day. The participant should be instructed to be as still as possible and remain quiet when assessing resting EEG. However, current EEG technology does permit EEG measures to be taken during exercise and sport performance. When the EEG data is collected, analog filters are used to limit the recording of low and high frequency signals outside the range of interest, such as low frequency signals from breathing. Nonetheless, prior to analyzing the EEG data, several steps must be taken to further ensure that the collected data is clean. Clean data most purely reflects the EEG data itself and does not include data that reflect muscle movement. Thus, in addition to the EEG electrodes, participants typically wear two electrodes placed around the outside of the eye to record eye blinks. Eye blinks and other muscle movement (e.g., from a cough, tensing muscles in the jaw) alter the EEG signal in a readily observable fashion and portions of the recording that contain these artifacts can be excluded prior to analysis using either manual or automated techniques. Once the data has been cleaned, it is then digitally filtered, which decreases extraneous data in the signal while maintaining the integrity of the EEG data. At this point, the data is ready for analysis.
Spontaneous EEG
There are four main wave forms measured by EEG: alpha, beta, theta, and delta. Alpha activity consists of waveforms that occur 8 to 12 times per second (Hz) and is interpreted as reflecting a relaxed state. Alpha activity tends to be low during mentally challenging situations. In sport psychology research, alpha activity has been associated with being relaxed and focused and mentally prepared for performance. EEG data has been used to distinguish mental states between novice and expert performers prior to task execution like a golf putt or free throw. Imagery training has also been linked to increased alpha activity. Biofeedback training has been used to teach participants to increase alpha activity with the expectation that this will result in better performance.
Beta waves (13–30Hz) are the most common type of EEG activity during wakefulness and are present during mental thought and activity, particularly during decision-making processes. Theta waves (4–8Hz) appear during drowsiness and light sleep. Delta waves (.5–3.5Hz) are found during periods of deep sleep and are characterized by very irregular and slow wave patterns. Delta waveforms are of particular interest to researchers exploring the effects of exercise on sleep quality.
In addition to interest in activity at a given site, there is also interest in examining hemispheric asymmetry in EEG responses. In the sport performance literature, expert performers typically display a quieting of left hemisphere activation, as inferred by greater EEG alpha power. This has been interpreted as being indicative of expert performers’ ability to block out distractions, unwanted emotions, and negative thoughts prior to motor responses and suggests that there is a causal link between this ability and performance. Exercise psychology literature has focused on EEG asymmetry as a marker of affective changes often associated with exercise. The cerebral lateralization hypothesis suggests that anxiety reductions and enhanced affect caused by exercise are due to a decrease in right, relative to left, hemisphere activation.
Event-Related Potentials
Event-related potentials (ERPs) are time-locked waveforms that are identified after averaging the EEG response recorded relative to a particular event. The event-related portion of the name expresses that the timing of the EEG activity is directly related (time-locked) to an event; this is typically a stimulus presentation (e.g., seeing or hearing a stimulus) or a voluntary motor response that is made (e.g., pushing a button). The EEG signal is averaged using the presentation of the stimulus as the anchor so that the patterns of activity are synchronized to the same event. The potential portion of the name expresses that ERPs reflect cumulative electrical potentials generated by neurons in the brain.
There are several different kinds of ERPs. ERPs that occur in response to a stimulus are called sensory-evoked potentials; ERPs that occur relative to a motor response are called motor potentials. A common experimental paradigm that is used to assess ERPs is the oddball paradigm. In this paradigm, the participant is asked to watch a computer monitor on which frequent stimuli (e.g., an X) and infrequent stimuli (e.g., an O) are displayed. The participant is instructed to respond as quickly as possible to one stimulus (e.g., the X) by pressing a button but is asked not to respond when the other stimulus (the O) is displayed. The EEG signal is time-locked to the presentation of the stimulus, which allows sensory-evoked potentials to be observed. Interpretations of ERP data are based on the amplitude of the potential (the vertical distance from the baseline activity to the peak or trough of the component) and the latency of the potential (the elapsed time to the peak amplitude of the component from the time-locked event). The amplitude and latency of the sensory evoked potential differ depending on whether the stimulus was the frequently occurring stimulus or the rarely occurring stimulus and also depending upon whether the participant responded correctly, for example, pressing the button when X was presented or incorrectly by pressing the button when O was presented to the stimulus. The motor potential is observed when the EEG signal is timelocked to the initiation of the motor response to press the button.
Two additional types of ERPs are referred to as slow ERPs because they occur over a relatively longer period of time than do the sensory-evoked and motor potential. Contingent negative variation (CNV) is observed when a participant is given a warning stimulus prior to presentation of a stimulus that is to be responded to, and its amplitude is increased by attention and decreased by distraction. A readiness potential is evident in the period prior to a voluntary movement and its amplitude has been shown to be related to motivation and to movement speed.
Once the data have been cleaned and averaged, the resultant waveforms are examined to identify the components of interest. The names of the components of the ERPs reflect the direction of the waveform (positive, P, or negative, N) relative to the baseline activity prior to the presentation of the stimulus and the approximate timing of the component relative to the stimulus. As previously described, components of the ERP are quantified based upon their amplitude and latency.
One ERP component that is of interest to sport and exercise psychology is the P300. The P300 is a positive waveform that occurs between 250 and 500 ms after the stimulus presentation. This component has been shown to be linked to the allocation of attention. The amplitude of the P300 is thought to be indicative of increased attention while the latency provides evidence of the time necessary to evaluate the stimulus (speed of cognitive processing). When considered simultaneously, the amplitude of the P300 is expected to be larger and the latency shorter when participants are using relatively few attentional resources to evaluate a stimulus and perform a task. The CNV (slow ERP) occurs approximately 260 to 470 ms after a warning stimulus and is a sustained negative component of the waveform. The CNV is thought to be indicative of a participant’s expectancy or anticipation of a stimulus. In the sport and exercise psychology literature, higher amplitude CNV has been linked to quicker reaction time.
References:
- Crabbe, J. B., & Dishman, R. K. (2004). Brain electrocortical activity during and after exercise:A quantitative synthesis. Psychophysiology, 41(4), 563–574.
- Hatfield, B. D., & Kerick, S. E. (2007). The psychology of superior sport performance: A cognitive and affective neuroscience perspective. In G. Tenenbaum & R. C. Eklund (Eds.), Handbook of sport psychology (3rd ed., pp. 84–112). Hoboken, NJ: Wiley.
- Niedermeyer, E., & Lopes Da Silva, F. H. (2005). Electroencephalography: Basic principles, clinical applications, and related fields. Philadelphia: Lippincott, Williams & Wilkins.
- Petruzzello, S. J., Ekkekakis, P., & Hall, E. E. (2006). Physical activity, affect, and electroencephalogram studies. In E. O. Acevedo & P. Ekkekakis (Eds.), Psychobiology of physical activity (pp. 111–128). Champaign, IL: Human Kinetics.
- Teplan, M. (2002). Fundamentals of EEG measurement. Measurement Science Review, 2(2), 1–11.
- Thompson, T., Steffert, T., Ros, T., Leach, J., & Gruzelier, J. (2008). EEG applications for sport and Methods, 45(4), 279–288.
See also:
- Sports Psychology
- Psychophysiology